Overview

Dataset statistics

Number of variables10
Number of observations385500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.4 MiB
Average record size in memory80.0 B

Variable types

Numeric10

Alerts

area[11] is highly overall correlated with area[13] and 3 other fieldsHigh correlation
area[13] is highly overall correlated with area[11] and 3 other fieldsHigh correlation
negpmax[13] is highly overall correlated with area[11] and 4 other fieldsHigh correlation
negpmax[14] is highly overall correlated with negpmax[13] and 1 other fieldsHigh correlation
pmax[13] is highly overall correlated with area[11] and 3 other fieldsHigh correlation
pmax[14] is highly overall correlated with area[11] and 4 other fieldsHigh correlation
tmax[11] is highly overall correlated with tmax[13]High correlation
tmax[13] is highly overall correlated with tmax[11]High correlation
negpmax[13] is highly skewed (γ1 = -270.4791604)Skewed
tmax[13] is highly skewed (γ1 = 24.10979066)Skewed
negpmax[14] is highly skewed (γ1 = 222.452793)Skewed
rms[11] has unique valuesUnique
rms[13] has unique valuesUnique

Reproduction

Analysis started2024-01-24 23:05:03.846223
Analysis finished2024-01-24 23:05:22.547761
Duration18.7 seconds
Software versionydata-profiling vv4.6.3
Download configurationconfig.json

Variables

area[11]
Real number (ℝ)

HIGH CORRELATION 

Distinct384469
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.735731
Minimum-0.85104126
Maximum95.228001
Zeros0
Zeros (%)0.0%
Negative8
Negative (%)< 0.1%
Memory size2.9 MiB
2024-01-25T00:05:22.621615image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-0.85104126
5-th percentile2.8328495
Q15.8064505
median9.013587
Q315.83488
95-th percentile35.503063
Maximum95.228001
Range96.079042
Interquartile range (IQR)10.028429

Descriptive statistics

Standard deviation10.309472
Coefficient of variation (CV)0.80949196
Kurtosis2.2151781
Mean12.735731
Median Absolute Deviation (MAD)4.0484808
Skewness1.5979274
Sum4909624.3
Variance106.28521
MonotonicityNot monotonic
2024-01-25T00:05:22.746127image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.677099609 3
 
< 0.1%
7.377392578 3
 
< 0.1%
2.971740723 3
 
< 0.1%
5.650927734 3
 
< 0.1%
7.238400879 3
 
< 0.1%
7.233789062 3
 
< 0.1%
10.81833496 2
 
< 0.1%
5.534521484 2
 
< 0.1%
2.610888672 2
 
< 0.1%
4.801262207 2
 
< 0.1%
Other values (384459) 385474
> 99.9%
ValueCountFrequency (%)
-0.8510412598 1
< 0.1%
-0.3863928223 1
< 0.1%
-0.256328125 1
< 0.1%
-0.2355834961 1
< 0.1%
-0.2106884766 1
< 0.1%
-0.05486816406 1
< 0.1%
-0.04532653809 1
< 0.1%
-0.04125 1
< 0.1%
0.09104980469 1
< 0.1%
0.2109594727 1
< 0.1%
ValueCountFrequency (%)
95.2280011 1
< 0.1%
92.34315247 1
< 0.1%
83.3121582 1
< 0.1%
77.14263 1
< 0.1%
76.90403015 1
< 0.1%
74.68208008 1
< 0.1%
72.22021973 1
< 0.1%
71.34995544 1
< 0.1%
69.47265564 1
< 0.1%
69.24884338 1
< 0.1%

tmax[11]
Real number (ℝ)

HIGH CORRELATION 

Distinct51190
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74.250317
Minimum0
Maximum204.6
Zeros53
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:05:22.853764image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile70.4
Q171
median71.6
Q372.2
95-th percentile94
Maximum204.6
Range204.6
Interquartile range (IQR)1.2

Descriptive statistics

Standard deviation20.631776
Coefficient of variation (CV)0.27786785
Kurtosis18.326898
Mean74.250317
Median Absolute Deviation (MAD)0.6
Skewness3.3790616
Sum28623497
Variance425.67018
MonotonicityNot monotonic
2024-01-25T00:05:22.960377image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71.6 31101
 
8.1%
72 30816
 
8.0%
71.2 30622
 
7.9%
71.4 30287
 
7.9%
71 30084
 
7.8%
72.2 29821
 
7.7%
71.8 29502
 
7.7%
70.8 26811
 
7.0%
72.4 24973
 
6.5%
70.6 16546
 
4.3%
Other values (51180) 104937
27.2%
ValueCountFrequency (%)
0 53
< 0.1%
0.4 51
< 0.1%
0.6 80
< 0.1%
0.8 50
< 0.1%
1 62
< 0.1%
1.2 58
< 0.1%
1.253945501 1
 
< 0.1%
1.4 66
< 0.1%
1.403961691 1
 
< 0.1%
1.419112428 1
 
< 0.1%
ValueCountFrequency (%)
204.6 42
< 0.1%
204.4 25
< 0.1%
204.2 30
< 0.1%
204 16
 
< 0.1%
203.8 15
 
< 0.1%
203.6 15
 
< 0.1%
203.4 7
 
< 0.1%
203.2 9
 
< 0.1%
203 14
 
< 0.1%
202.9402183 1
 
< 0.1%

rms[11]
Real number (ℝ)

UNIQUE 

Distinct385500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4153145
Minimum0.31274287
Maximum5.9888774
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:05:23.065672image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0.31274287
5-th percentile0.87492307
Q11.1614107
median1.3913401
Q31.6430275
95-th percentile2.0370042
Maximum5.9888774
Range5.6761345
Interquartile range (IQR)0.48161687

Descriptive statistics

Standard deviation0.3565512
Coefficient of variation (CV)0.25192365
Kurtosis0.89421435
Mean1.4153145
Median Absolute Deviation (MAD)0.23972846
Skewness0.47083911
Sum545603.74
Variance0.12712875
MonotonicityNot monotonic
2024-01-25T00:05:23.170678image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9041567568 1
 
< 0.1%
1.58038554 1
 
< 0.1%
1.269294734 1
 
< 0.1%
1.153712572 1
 
< 0.1%
0.935886592 1
 
< 0.1%
1.230480761 1
 
< 0.1%
1.227548427 1
 
< 0.1%
0.9505139487 1
 
< 0.1%
1.555386265 1
 
< 0.1%
1.223129351 1
 
< 0.1%
Other values (385490) 385490
> 99.9%
ValueCountFrequency (%)
0.3127428691 1
< 0.1%
0.3185457968 1
< 0.1%
0.3300341591 1
< 0.1%
0.335154207 1
< 0.1%
0.3439381627 1
< 0.1%
0.3555530482 1
< 0.1%
0.3593076998 1
< 0.1%
0.3660599009 1
< 0.1%
0.3682568085 1
< 0.1%
0.3716994765 1
< 0.1%
ValueCountFrequency (%)
5.988877405 1
< 0.1%
5.721379868 1
< 0.1%
5.511302507 1
< 0.1%
5.485954148 1
< 0.1%
5.485235551 1
< 0.1%
5.398295036 1
< 0.1%
5.234579293 1
< 0.1%
5.225698497 1
< 0.1%
5.117566305 1
< 0.1%
5.098328992 1
< 0.1%

pmax[13]
Real number (ℝ)

HIGH CORRELATION 

Distinct382707
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.233983
Minimum2.7270477
Maximum141.53091
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:05:23.287148image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum2.7270477
5-th percentile10.241735
Q117.327409
median33.571727
Q360.328537
95-th percentile96.301949
Maximum141.53091
Range138.80387
Interquartile range (IQR)43.001128

Descriptive statistics

Standard deviation27.992784
Coefficient of variation (CV)0.67887655
Kurtosis-0.284763
Mean41.233983
Median Absolute Deviation (MAD)18.912434
Skewness0.81725413
Sum15895700
Variance783.59595
MonotonicityNot monotonic
2024-01-25T00:05:23.403387image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13.19282227 3
 
< 0.1%
11.83750916 3
 
< 0.1%
15.90348511 3
 
< 0.1%
14.12488098 3
 
< 0.1%
46.03769226 3
 
< 0.1%
21.46132507 3
 
< 0.1%
26.91636047 3
 
< 0.1%
12.34752502 3
 
< 0.1%
12.47222595 3
 
< 0.1%
17.65672607 3
 
< 0.1%
Other values (382697) 385470
> 99.9%
ValueCountFrequency (%)
2.727047729 1
< 0.1%
3.064413452 1
< 0.1%
3.605279541 1
< 0.1%
3.694827271 1
< 0.1%
3.743627951 1
< 0.1%
3.839797718 1
< 0.1%
3.849533081 1
< 0.1%
3.860357666 1
< 0.1%
3.965130615 1
< 0.1%
3.975018311 1
< 0.1%
ValueCountFrequency (%)
141.5309143 1
< 0.1%
138.77117 1
< 0.1%
138.5662292 1
< 0.1%
138.563504 1
< 0.1%
137.49758 1
< 0.1%
137.0080078 1
< 0.1%
136.998233 1
< 0.1%
136.442334 1
< 0.1%
136.1855927 1
< 0.1%
134.883725 1
< 0.1%

negpmax[13]
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct380014
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-22.280679
Minimum-14186.921
Maximum-1.3402512
Zeros0
Zeros (%)0.0%
Negative385500
Negative (%)100.0%
Memory size2.9 MiB
2024-01-25T00:05:23.615562image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-14186.921
5-th percentile-58.6454
Q1-33.413062
median-16.31893
Q3-7.2241821
95-th percentile-4.615182
Maximum-1.3402512
Range14185.581
Interquartile range (IQR)26.18888

Descriptive statistics

Standard deviation35.573168
Coefficient of variation (CV)-1.5965926
Kurtosis100951.18
Mean-22.280679
Median Absolute Deviation (MAD)10.314912
Skewness-270.47916
Sum-8589201.8
Variance1265.4503
MonotonicityNot monotonic
2024-01-25T00:05:23.724103image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-5.129528809 4
 
< 0.1%
-6.357565308 4
 
< 0.1%
-4.923834229 3
 
< 0.1%
-6.673403931 3
 
< 0.1%
-5.679980469 3
 
< 0.1%
-6.255175781 3
 
< 0.1%
-12.12822571 3
 
< 0.1%
-5.072729492 3
 
< 0.1%
-8.182781982 3
 
< 0.1%
-5.266827393 3
 
< 0.1%
Other values (380004) 385468
> 99.9%
ValueCountFrequency (%)
-14186.92083 1
< 0.1%
-12193.05913 1
< 0.1%
-2873.89555 1
< 0.1%
-2634.812908 1
< 0.1%
-1826.826656 1
< 0.1%
-244.3120188 1
< 0.1%
-160.0252238 1
< 0.1%
-83.96565247 1
< 0.1%
-83.51788635 1
< 0.1%
-82.89954224 1
< 0.1%
ValueCountFrequency (%)
-1.340251241 1
< 0.1%
-1.649971296 1
< 0.1%
-1.823561528 1
< 0.1%
-1.858462811 1
< 0.1%
-1.87787212 1
< 0.1%
-1.983622516 1
< 0.1%
-1.985220457 1
< 0.1%
-2.105595419 1
< 0.1%
-2.121166073 1
< 0.1%
-2.121277267 1
< 0.1%

area[13]
Real number (ℝ)

HIGH CORRELATION 

Distinct384882
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.437697
Minimum1.107431
Maximum120.17597
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:05:23.829899image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum1.107431
5-th percentile6.831275
Q111.582386
median19.268355
Q331.428853
95-th percentile47.841777
Maximum120.17597
Range119.06854
Interquartile range (IQR)19.846468

Descriptive statistics

Standard deviation13.082657
Coefficient of variation (CV)0.58306594
Kurtosis-0.33250461
Mean22.437697
Median Absolute Deviation (MAD)8.9924475
Skewness0.74285918
Sum8649732
Variance171.15591
MonotonicityNot monotonic
2024-01-25T00:05:23.941142image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13.02888489 3
 
< 0.1%
48.59344238 2
 
< 0.1%
21.80147705 2
 
< 0.1%
9.663457031 2
 
< 0.1%
28.35120056 2
 
< 0.1%
11.14979126 2
 
< 0.1%
7.444812012 2
 
< 0.1%
9.432836914 2
 
< 0.1%
17.69620972 2
 
< 0.1%
7.958648682 2
 
< 0.1%
Other values (384872) 385479
> 99.9%
ValueCountFrequency (%)
1.10743103 1
< 0.1%
1.389016113 1
< 0.1%
1.505531006 1
< 0.1%
1.507468262 1
< 0.1%
1.533605957 1
< 0.1%
1.558155518 1
< 0.1%
1.629433594 1
< 0.1%
1.773081055 1
< 0.1%
1.782971191 1
< 0.1%
1.788989258 1
< 0.1%
ValueCountFrequency (%)
120.1759735 1
< 0.1%
103.3779846 1
< 0.1%
101.235437 1
< 0.1%
96.17752686 1
< 0.1%
85.15785217 1
< 0.1%
83.38744629 1
< 0.1%
81.79850586 1
< 0.1%
80.68242249 1
< 0.1%
78.87852783 1
< 0.1%
78.55229736 1
< 0.1%

tmax[13]
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct17384
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.709501
Minimum0
Maximum204
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:05:24.049664image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile70.8
Q171.2
median71.6
Q372.2
95-th percentile72.6
Maximum204
Range204
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.9649762
Coefficient of variation (CV)0.041347047
Kurtosis968.02554
Mean71.709501
Median Absolute Deviation (MAD)0.4
Skewness24.109791
Sum27644013
Variance8.7910836
MonotonicityNot monotonic
2024-01-25T00:05:24.162136image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71.2 37999
9.9%
71.6 37788
9.8%
72 37467
9.7%
71.4 36839
9.6%
72.2 36533
9.5%
71.8 35816
9.3%
71 34365
8.9%
72.4 34098
8.8%
70.8 29598
7.7%
72.6 19932
5.2%
Other values (17374) 45065
11.7%
ValueCountFrequency (%)
0 1
 
< 0.1%
0.4 2
< 0.1%
0.6 1
 
< 0.1%
0.8 3
< 0.1%
1.4 1
 
< 0.1%
3.2 1
 
< 0.1%
4.2 4
< 0.1%
4.8 2
< 0.1%
4.995365196 1
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
204 1
 
< 0.1%
202.6 1
 
< 0.1%
201.8 1
 
< 0.1%
201.2 2
< 0.1%
201 3
< 0.1%
200.8313639 1
 
< 0.1%
200.8 3
< 0.1%
200.7919853 1
 
< 0.1%
200.6 1
 
< 0.1%
200.4 2
< 0.1%

rms[13]
Real number (ℝ)

UNIQUE 

Distinct385500
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4116071
Minimum0.32766421
Maximum6.283808
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:05:24.270293image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0.32766421
5-th percentile0.868752
Q11.1567125
median1.3865315
Q31.6400555
95-th percentile2.0383014
Maximum6.283808
Range5.9561438
Interquartile range (IQR)0.48334295

Descriptive statistics

Standard deviation0.35842312
Coefficient of variation (CV)0.25391138
Kurtosis0.8545296
Mean1.4116071
Median Absolute Deviation (MAD)0.24077128
Skewness0.47157058
Sum544174.55
Variance0.12846713
MonotonicityNot monotonic
2024-01-25T00:05:24.375934image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.184943091 1
 
< 0.1%
0.9165588068 1
 
< 0.1%
0.8233029842 1
 
< 0.1%
1.57173268 1
 
< 0.1%
1.181254343 1
 
< 0.1%
1.232111075 1
 
< 0.1%
2.098542586 1
 
< 0.1%
1.137175464 1
 
< 0.1%
1.305321252 1
 
< 0.1%
2.029882322 1
 
< 0.1%
Other values (385490) 385490
> 99.9%
ValueCountFrequency (%)
0.3276642062 1
< 0.1%
0.3363663184 1
< 0.1%
0.3493638045 1
< 0.1%
0.3631198407 1
< 0.1%
0.3638868167 1
< 0.1%
0.3721241383 1
< 0.1%
0.3736989799 1
< 0.1%
0.3761909149 1
< 0.1%
0.3795613424 1
< 0.1%
0.3826597675 1
< 0.1%
ValueCountFrequency (%)
6.283808014 1
< 0.1%
6.250925281 1
< 0.1%
5.872300283 1
< 0.1%
5.663247721 1
< 0.1%
5.250220932 1
< 0.1%
5.187480287 1
< 0.1%
5.180491321 1
< 0.1%
5.153746046 1
< 0.1%
4.983333525 1
< 0.1%
4.928396164 1
< 0.1%

pmax[14]
Real number (ℝ)

HIGH CORRELATION 

Distinct377962
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.656853
Minimum1.8016388
Maximum115.792
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:05:24.480765image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum1.8016388
5-th percentile4.163501
Q15.7205575
median10.125145
Q318.72063
95-th percentile60.640518
Maximum115.792
Range113.99037
Interquartile range (IQR)13.000072

Descriptive statistics

Standard deviation17.784631
Coefficient of variation (CV)1.0677066
Kurtosis5.316419
Mean16.656853
Median Absolute Deviation (MAD)4.9933837
Skewness2.3257143
Sum6421216.9
Variance316.29311
MonotonicityNot monotonic
2024-01-25T00:05:24.590825image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.949716187 4
 
< 0.1%
5.380264282 3
 
< 0.1%
5.039877319 3
 
< 0.1%
5.374301147 3
 
< 0.1%
5.023007202 3
 
< 0.1%
12.46167603 3
 
< 0.1%
5.840423584 3
 
< 0.1%
6.379003906 3
 
< 0.1%
4.035028076 3
 
< 0.1%
5.165966797 3
 
< 0.1%
Other values (377952) 385469
> 99.9%
ValueCountFrequency (%)
1.801638794 1
< 0.1%
1.873745728 1
< 0.1%
2.001589966 1
< 0.1%
2.094113159 1
< 0.1%
2.112582397 1
< 0.1%
2.11914978 1
< 0.1%
2.131115723 1
< 0.1%
2.179855347 1
< 0.1%
2.205877686 1
< 0.1%
2.227529907 1
< 0.1%
ValueCountFrequency (%)
115.7920044 1
< 0.1%
114.3332611 1
< 0.1%
114.0329559 1
< 0.1%
113.9634644 1
< 0.1%
113.3895233 1
< 0.1%
113.1857544 1
< 0.1%
113.1255981 1
< 0.1%
112.6525238 1
< 0.1%
112.4599945 1
< 0.1%
112.4030182 1
< 0.1%

negpmax[14]
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct365576
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-9.8652945
Minimum-39039.395
Maximum74812.277
Zeros0
Zeros (%)0.0%
Negative385499
Negative (%)> 99.9%
Memory size2.9 MiB
2024-01-25T00:05:24.697884image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-39039.395
5-th percentile-35.897436
Q1-8.2070056
median-5.6508922
Q3-4.7993722
95-th percentile-3.8911559
Maximum74812.277
Range113851.67
Interquartile range (IQR)3.4076334

Descriptive statistics

Standard deviation152.73595
Coefficient of variation (CV)-15.482148
Kurtosis169100.87
Mean-9.8652945
Median Absolute Deviation (MAD)1.1031694
Skewness222.45279
Sum-3803071
Variance23328.269
MonotonicityNot monotonic
2024-01-25T00:05:24.804787image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-5.71133728 5
 
< 0.1%
-5.206564331 5
 
< 0.1%
-5.335623169 5
 
< 0.1%
-4.766656494 5
 
< 0.1%
-5.799734497 5
 
< 0.1%
-4.728585815 5
 
< 0.1%
-4.420578003 4
 
< 0.1%
-4.085986328 4
 
< 0.1%
-4.646548462 4
 
< 0.1%
-4.952313232 4
 
< 0.1%
Other values (365566) 385454
> 99.9%
ValueCountFrequency (%)
-39039.3947 1
< 0.1%
-36273.81597 1
< 0.1%
-16084.10489 1
< 0.1%
-9560.21634 1
< 0.1%
-9382.374572 1
< 0.1%
-6324.974212 1
< 0.1%
-2918.523508 1
< 0.1%
-2788.010868 1
< 0.1%
-2657.907628 1
< 0.1%
-2053.439122 1
< 0.1%
ValueCountFrequency (%)
74812.27737 1
< 0.1%
-0.02359893961 1
< 0.1%
-1.364963863 1
< 0.1%
-1.376395027 1
< 0.1%
-1.407587002 1
< 0.1%
-1.41823263 1
< 0.1%
-1.444069894 1
< 0.1%
-1.453838999 1
< 0.1%
-1.504335684 1
< 0.1%
-1.596983213 1
< 0.1%

Interactions

2024-01-25T00:05:20.582258image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:09.861832image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:11.136471image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:12.316975image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:13.516175image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:14.714675image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:15.940536image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:17.077704image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:18.210762image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:19.319511image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:20.701278image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:09.974756image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:11.250482image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:12.431068image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:13.630200image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:14.824213image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:16.064195image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:17.185292image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:18.319450image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:19.426591image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:20.822407image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:10.091084image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:11.363474image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:12.548129image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:13.751701image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:14.933814image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:16.172289image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:17.295157image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:18.422930image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:19.536902image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:20.948330image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:10.207929image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:11.484039image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:12.662008image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:13.865167image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:15.045106image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:16.280162image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:17.407395image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:18.530745image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:19.643747image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:21.064049image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:10.423566image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:11.606150image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:12.788697image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:13.990326image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:15.157446image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:16.390805image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:17.521030image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:18.644060image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:19.859846image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:21.192071image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:10.540959image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:11.733786image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:12.911815image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:14.115164image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:15.273990image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:16.505594image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:17.639649image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:18.762056image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:19.982663image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:21.314839image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:10.659787image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:11.845384image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:13.032769image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:14.230375image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:15.480700image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:16.618051image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:17.750673image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:18.877706image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:20.105947image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:21.440003image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:10.784384image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:11.963641image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:13.158118image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:14.357856image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:15.597156image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:16.738563image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:17.868298image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:18.989671image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:20.225255image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:21.557716image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:10.898169image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:12.086357image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:13.276070image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:14.478525image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:15.711725image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:16.848873image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:17.983264image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:19.097735image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:20.342228image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:21.676367image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:11.018800image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:12.201818image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:13.391711image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:14.596000image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:15.824712image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:16.960647image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:18.096860image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:19.207056image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:05:20.461692image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Correlations

2024-01-25T00:05:24.877672image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
area[11]area[13]negpmax[13]negpmax[14]pmax[13]pmax[14]rms[11]rms[13]tmax[11]tmax[13]
area[11]1.0000.505-0.514-0.4630.5220.6500.000-0.001-0.179-0.100
area[13]0.5051.000-0.937-0.4730.9780.795-0.0000.000-0.092-0.184
negpmax[13]-0.514-0.9371.0000.509-0.964-0.8020.001-0.0000.1020.190
negpmax[14]-0.463-0.4730.5091.000-0.483-0.5960.0030.0040.1060.094
pmax[13]0.5220.978-0.964-0.4831.0000.8120.0000.001-0.098-0.191
pmax[14]0.6500.795-0.802-0.5960.8121.0000.0000.000-0.120-0.153
rms[11]0.000-0.0000.0010.0030.0000.0001.0000.006-0.0060.001
rms[13]-0.0010.000-0.0000.0040.0010.0000.0061.0000.000-0.000
tmax[11]-0.179-0.0920.1020.106-0.098-0.120-0.0060.0001.0000.787
tmax[13]-0.100-0.1840.1900.094-0.191-0.1530.001-0.0000.7871.000

Missing values

2024-01-25T00:05:21.794419image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-25T00:05:22.026678image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

area[11]tmax[11]rms[11]pmax[13]negpmax[13]area[13]tmax[13]rms[13]pmax[14]negpmax[14]
07.61137672.20.9041577.454877-16.8611634.19190972.6000001.1849436.611877-17.685799
18.025536119.61.20103918.472514-3.37232416.620582119.8125121.57800913.802252-5.154840
24.51731671.81.9953947.336668-5.74238311.79225871.9082121.3330365.940039-3.860550
35.92739072.21.4916108.450671-6.3421144.49674172.6000001.9450656.434910-5.576315
47.38607771.01.3188738.721952-4.3964369.12713671.4115351.5139884.483080-5.361823
54.93042871.00.8714467.639423-5.0533935.20975871.4000001.3514403.760919-5.605902
65.62201872.00.7143997.822296-4.3678894.75745872.4000001.3686664.451303-5.102408
77.44696972.21.4906229.386575-4.9795755.49447372.6000001.4520405.312753-4.244864
82.79060171.61.79825610.736859-5.5583606.03023972.0000001.0296535.130885-4.701236
93.97242470.81.2297586.943546-4.2993133.46863271.2000002.2564583.861499-6.045334
area[11]tmax[11]rms[11]pmax[13]negpmax[13]area[13]tmax[13]rms[13]pmax[14]negpmax[14]
3854901.9711161.4000001.82369718.704639-6.16842012.73011272.4631111.1400939.882791-6.206964
3854911.139029187.8000001.02502819.139969-8.28923011.27180872.0000001.56587510.375104-6.018223
3854925.528488128.0000001.23644318.910306-7.49887412.32653771.6000001.45271610.458133-4.735043
3854931.703162111.6000001.22753020.207239-11.26669913.34190471.4000000.9361448.793121-7.426369
3854946.04487072.2790721.14952319.617819-5.82859213.09603572.2000001.40152210.386407-4.634589
3854951.990222204.4000001.06195919.454065-7.53140910.65076271.4000000.9644905.842563-4.147369
38549611.75826872.2000001.33098617.604636-5.50572512.82719571.5003141.63249711.819031-5.125480
3854974.86244171.5769522.04418620.783524-6.31840513.98132071.6000001.94462610.120659-3.479907
3854989.01770672.0000002.05286614.048267-6.91560111.84600371.6000001.28615010.754880-5.030399
38549918.54792571.8614201.22457321.256503-17.55917115.06958972.0000000.7344426.895911-20.049325